Sample6 CONTROL: Building the Bridge to DETECT and Beyond

When we built Sample6 CONTROL, our focus was helping to solve the challenge of managing environmental data. We met customers with giant and complex Excel spreadsheets and paper floorplans with sticky notes. We knew that we could offer a better solution. The first step was to sort out the challenges that food processors were facing:

So . . .Much . . .Data

One of the reasons that environmental tracking is such a challenge is the volume and diversity of the data. A typical environmental tracking program is testing 10-15 samples per week per line. Many are 3-4 times that and that is just for pathogen detection. Then, layer on routine testing like EB and yeast plate counts, followed by sanitation data like ATP.

Comparing apples and oranges

Some results are positive vs. negative.

Others are pass/fail.

Some are numeric counts like ATP.

Still others have qualitative elements like plate reads.

How do you reconcile all this?

Lost in Translation

Reports from outside labs arrive in pdf. Data from internal plate counts are tracked in a spreadsheet. Data from ATP is utilized by sanitation and in some cases captured by hand, in others it is exported as a spreadsheet. To get this data into one place often leads to pain-staking(and error prone) data entry.

So how do you solve this?

Flexible Data Base

Based on customer feedback, we’ve added count fields, notes fields and different determination options. Our goal is build a flexible platform and that supports all environmental data. Are there other pieces missing? Let us know. We use an agile development process that enables us to incorporate customer requests quickly into our software.

Automation

We built CONTROL and DETECT to work seamlessly together so that the large volume of data, could be entered automatically into CONTROL. Sample6 DETECT results are generated by the DETECT Reader, a commercially available luminometer. The Sample6 DETECT Reader is directed by a small desktop application, which converts the numbers generated from the machine into Presumed Positives and Negatives. These results are linked to a schedule generated in CONTROL and automatically uploaded.

Here’s how:

Users have a log in for both CONTROL and DETECT Reader.

Outcome

Sounds like magic?

We are able to do this through an API (Application Programming Interface) between CONTROL and the Reader. An API is a bridge between the two applications. Once in place, communication and data can easily be transferred. This API can be used to connect CONTROL to other applications as well and we are starting to work with other systems as well.

At Sample6, we want to make food safer through easy to use technologies. Historical environmental data is a critical piece of this. We also have a data uploader so that you can import your spreadsheets to take advantage of the tools and workflows in CONTROL.